Noise Suppression Algorithm for High Precision Seismic Data Acquirement System

Abstract

Data acquirement system is key instrument to record seismic data in the field of seismic research. Seismic wave data collected by data acquirement system are mixed with effective wave and interference noise. Noise suppression is an important step in seismic data processing in data acquirement system, especially in high precision application, which will decrease the precision of seismic records from geophone. The accuracy of geophone and seismic instrument and precision of data acquirement system determine the total precision of seismic data records. A problem of collecting seismic data is how to select a suitable method to reserve effective wave and eliminate interference noise. Existing methods for distinguishing effective wave from interference noise are based on predefined noise frequency on the basis of experience, which is time-consuming, relying on mass data analysis, and will lead to suppress useful wave information near noise frequency. In this work, a noise identification and suppression algorithm based on one layer neural network is advocated. Using noise suppression algorithm presented in this work iteratively, the root-mean-square of processed data is decrease to 0.84uV, which means the signal-noise-ratio 135.5dB in practice. The results have proved effective separation of signals from noise and can satisfy the requirements of precision seismic data acquirement system.